EP1492081B1 - A system and method for simulation of non-linear audio equipment - Google Patents
A system and method for simulation of non-linear audio equipment Download PDFInfo
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- EP1492081B1 EP1492081B1 EP04102813.5A EP04102813A EP1492081B1 EP 1492081 B1 EP1492081 B1 EP 1492081B1 EP 04102813 A EP04102813 A EP 04102813A EP 1492081 B1 EP1492081 B1 EP 1492081B1
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- signal
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- dynamic
- recited
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10H—ELECTROPHONIC MUSICAL INSTRUMENTS; INSTRUMENTS IN WHICH THE TONES ARE GENERATED BY ELECTROMECHANICAL MEANS OR ELECTRONIC GENERATORS, OR IN WHICH THE TONES ARE SYNTHESISED FROM A DATA STORE
- G10H1/00—Details of electrophonic musical instruments
- G10H1/02—Means for controlling the tone frequencies, e.g. attack or decay; Means for producing special musical effects, e.g. vibratos or glissandos
- G10H1/06—Circuits for establishing the harmonic content of tones, or other arrangements for changing the tone colour
- G10H1/16—Circuits for establishing the harmonic content of tones, or other arrangements for changing the tone colour by non-linear elements
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10H—ELECTROPHONIC MUSICAL INSTRUMENTS; INSTRUMENTS IN WHICH THE TONES ARE GENERATED BY ELECTROMECHANICAL MEANS OR ELECTRONIC GENERATORS, OR IN WHICH THE TONES ARE SYNTHESISED FROM A DATA STORE
- G10H3/00—Instruments in which the tones are generated by electromechanical means
- G10H3/12—Instruments in which the tones are generated by electromechanical means using mechanical resonant generators, e.g. strings or percussive instruments, the tones of which are picked up by electromechanical transducers, the electrical signals being further manipulated or amplified and subsequently converted to sound by a loudspeaker or equivalent instrument
- G10H3/14—Instruments in which the tones are generated by electromechanical means using mechanical resonant generators, e.g. strings or percussive instruments, the tones of which are picked up by electromechanical transducers, the electrical signals being further manipulated or amplified and subsequently converted to sound by a loudspeaker or equivalent instrument using mechanically actuated vibrators with pick-up means
- G10H3/18—Instruments in which the tones are generated by electromechanical means using mechanical resonant generators, e.g. strings or percussive instruments, the tones of which are picked up by electromechanical transducers, the electrical signals being further manipulated or amplified and subsequently converted to sound by a loudspeaker or equivalent instrument using mechanically actuated vibrators with pick-up means using a string, e.g. electric guitar
- G10H3/186—Means for processing the signal picked up from the strings
- G10H3/187—Means for processing the signal picked up from the strings for distorting the signal, e.g. to simulate tube amplifiers
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10H—ELECTROPHONIC MUSICAL INSTRUMENTS; INSTRUMENTS IN WHICH THE TONES ARE GENERATED BY ELECTROMECHANICAL MEANS OR ELECTRONIC GENERATORS, OR IN WHICH THE TONES ARE SYNTHESISED FROM A DATA STORE
- G10H2210/00—Aspects or methods of musical processing having intrinsic musical character, i.e. involving musical theory or musical parameters or relying on musical knowledge, as applied in electrophonic musical tools or instruments
- G10H2210/155—Musical effects
- G10H2210/311—Distortion, i.e. desired non-linear audio processing to change the tone color, e.g. by adding harmonics or deliberately distorting the amplitude of an audio waveform
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10H—ELECTROPHONIC MUSICAL INSTRUMENTS; INSTRUMENTS IN WHICH THE TONES ARE GENERATED BY ELECTROMECHANICAL MEANS OR ELECTRONIC GENERATORS, OR IN WHICH THE TONES ARE SYNTHESISED FROM A DATA STORE
- G10H2250/00—Aspects of algorithms or signal processing methods without intrinsic musical character, yet specifically adapted for or used in electrophonic musical processing
- G10H2250/131—Mathematical functions for musical analysis, processing, synthesis or composition
- G10H2250/165—Polynomials, i.e. musical processing based on the use of polynomials, e.g. distortion function for tube amplifier emulation, filter coefficient calculation, polynomial approximations of waveforms, physical modeling equation solutions
- G10H2250/175—Jacobi polynomials of several variables, e.g. Heckman-Opdam polynomials, or of one variable only, e.g. hypergeometric polynomials
- G10H2250/181—Gegenbauer or ultraspherical polynomials, e.g. for harmonic analysis
- G10H2250/191—Chebyshev polynomials, e.g. to provide filter coefficients for sharp rolloff filters
Definitions
- the present invention relates generally to a system for non-linear audio equipment simulation, and more specifically to the estimation of characteristic parameters in a model of such equipment and real-time simulation of this model.
- a dynamic system can be any physical or abstract process where one can observe its input and the outputs the process produces. Audio equipment and in particular a tube amplifier fits very well in this framework and is no exception to this general problem.
- Audio equipment that can be controlled by potentiometers can be simulated in software by using a number of fixed filters, and then interpolating between these.
- a piece of prior art is the US patent 6,222,110 , which describes a method for interpolating two second order filters.
- the problem to be solved and the object of the invention is to provide an improved method and system for simulating audio equipment in general and tube amplifiers in particular, for instance those found in electric guitar equipment. Aspects of the problem are:
- the characteristic behavior of the audio equipment is modeled as a dynamic non-linearity (DNL), where a mode parameter decides which SNL should be active.
- DNS dynamic non-linearity
- This mode parameter can be interpreted as the operating point of the audio device and it may for instance include hysteresis effects and the temperature, measured as the recent energy.
- the invention comprises a particular structure on the DNL, which is built up from a linear combination of a basis for the SNL, where the so called Chebyshev polynomial basis is one possible choice.
- This gives many practical advantages for both identification and simulation performance, as will be described later.
- An important consequence, compared to related art, is that the particular structure that is used does not require over-sampling.
- the invention also comprises an efficient identification experiment for estimating the coefficients in the Chebyshev expansion, or any other basis expansion, of the DNL.
- no known standard structure is perfectly suitable for high-performance tube amplifiers.
- prior art there is therefore a lack of satisfying models for simulating tube amplifiers in a natural sounding manner.
- Our findings is that standardized model structures consisting of series connection of linear dynamics and static non-linearities (SNL's) cannot model the complicated behavior of for instance tubes
- Audio equipment that can be controlled by potentiometers can be simulated in software by using a number of fixed filters, and then interpolating between these.
- a piece of prior art is the US patent 6,222,110 , which describes a method for interpolating two second order filters.
- the problem to be solved and the object of the invention is to provide an improved method and system for simulating audio equipment in general and tube amplifiers in particular, for instance those found in electric guitar equipment. Aspects of the problem are:
- the characteristic behavior of the audio equipment is modeled as a dynamic non-linearity (DNL), where a mode parameter decides which SNL should be active.
- DNS dynamic non-linearity
- This mode parameter can be interpreted as the operating point of the audio device and it may for instance include hysteresis effects and the temperature, measured as the recent energy.
- the invention comprises a particular structure on the DNL, which is built up from a linear combination of a basis for the SNL, where the so called Chebyshev polynomial basis is one possible choice.
- This gives many practical advantages for both identification and simulation performance, as will be described later.
- An important consequence, compared to related art, is that the particular structure that is used does not require over-sampling.
- the invention also comprises an efficient identification experiment for estimating the coefficients in the Chebyshev expansion, or any other basis expansion, of the DNL.
- an efficient identification experiment for estimating the coefficients in the Chebyshev expansion, or any other basis expansion, of the DNL.
- inputting sinusoids of different amplitudes is sufficient for estimation of these coefficients, and it is shown that these are related to the Fourier series expansion of the measured output of the audio equipment, enabling efficient algorithms, such as the fast Fourier transform (FFT) or more dedicated algorithms to be used.
- FFT fast Fourier transform
- the present disclosure describes an apparatus for software or hardware emulation of electronic audio equipment, which characterizes a non-linear behavior.
- the invention comprises an analog to digital interface (504) for the input audio signal (502), whose output (506) is communicatively coupled to a dynamic non-linearity (508).
- the output (514) of this dynamic non-linearity is finally communicatively coupled to an interface (516) producing the output audio signal (518).
- the dynamic non-linearity consists of mode switching static non-linear function, where the mode parameter (512) is estimated in a function (510) based on the previous values on the input (506) and output (514) of the dynamic non-linearity.
- a linear filter is used to change the frequency content of the interfaced audio signal (504) before it is coupled to the DNL (508).
- Yet another linear filter can be used on the DNL's output (514) to change the audio output frequency characteristics.
- the invention is based on a model of first the linear parts and then a dynamic non-linear model structure for the non-linear devices, identification of the free parameters in this non-linear model structure and finally a way to simulate this model.
- the total audio equipment emulator is outlined in FIG 1 .
- FIG 6 a guitar (302) is connected to a pre-amplifier (304), whose output is power amplified (306) and fed to the speakers (308).
- a tube can be seen to be a typical non-linear audio equipment in this context.
- the invention comprises a method and a realization of the method that may be realized in hardware, software or a combination thereof.
- the most feasible realization of the invention is likely to be in the shape of a computer program product preferably comprising a data carrier provided with program code or other means devised to control or direct a data processing apparatus to perform the method steps and functions in accordance with the description.
- a data processing apparatus running the inventive method typically includes a central processing unit, data storage means and an I/O-interface for signals or parameter values.
- the invention may also be realized as specifically designed hardware and software in an apparatus or a system comprising mechanisms and functional stages or other means carrying out the method steps and functions in accordance with the description.
- An embodiment of the invention comprises modeling of linear parts in the electronic device, denoted G pre (102) in FIG 1 .
- the modeling of linear dynamics is preferably carried out in a per se known manner, for example shown in the above cited prior art.
- the parts of the amplifier that include only passive components like resistors and capacitors, can be modeled theoretically with high accuracy, at least if all component values are known.
- the procedure to model and simulate the linear part is well-known from for instance the text books above, but is an important preliminary step for this invention.
- the electrical circuit with passive components will provide a continuous time filter.
- G s d 0 s m + d 1 s m ⁇ 1 + ... + d m s n + c 1 s n ⁇ 1 + ... + c n
- v nom denote the nominal component values.
- the parameters d i and c i can be computed from the known component values.
- this model can be converted to a discrete time model H ( z ; ⁇ ).
- ⁇ ( a 1 , a 2 , ..., a n , b 0 , b 1 , ..., b m ) T .
- ⁇ ( a 1 , a 2 , ..., a n , b 0 , b 1 , ..., b m ) T .
- ⁇ ( a 1 , a 2 , ..., a n , b 0 , b 1 , ..., b m )
- the second method applies in the frequency domain, see e.g.
- Equation (1) Computing the structure in equation (1) and then equation (2) from a circuit scheme is a quite tedious task to do for each new amplifier that is going to be modeled.
- An alternative used in an embodiment of the invention is to establish a general black-box model of the form as in equation (2), where one guesses or uses model selection criteria to choose m and n, collect input-output data in an identification experiment and then estimate the parameters with standard methods, for instance available in the system identification or frequency domain identification toolboxes in Matlab. This will provide an H (z; ⁇ ).
- a flexible linear part in an electronic device, G pre (102) and G eq (126) in FIG 1 can be controlled by the user by turning potentiometers. Such a change influences all coefficients in the filter H(z) in Equation (2), which thus has to be recalculated.
- One way to avoid this, is to compute the filter H (z) for a number of potentiometer settings, and then interpolate between these. This is important for equalizers and tonestacks, which usually have 3-4 different potentiometers controlling the tone.
- Another interesting application is to let a pedal or the output from another control unit replace the potentiometers.
- the linear filter should be interpolated from tabled filters. Below, an accurate method with little memory requirement is described.
- the number of pre-computed filter coefficients that need to be stored in memory is too high.
- Ten different potentiometer settings for four potentiometers implies 10 4 set of filter coefficients.
- the non-linear function f i is preferably stored as a table and one-dimensional interpolation applied. Here, only 2 4 different coefficient sets need to be pre-computed and stored in memory. Practice has shown that audio equipment as tone stacks are interpolated very accurately with this method.
- Equation (2) The linear parts in the electronic device, denoted G pre (102) and G eq (126) in FIG 1 , are subject to numerical ill-conditioning. Simulating Equation (2) can result in an unstable output, or at least not as accurate as desirable. This is in particular a problem for highly resonant audio devices as loudspeakers.
- An embodiment of the invention comprises the use of numerically robust basis functions and delta operators as outlined below.
- any linear transfer function can be described as a sum of a basis function expansion.
- the basis functions can for instance be second order orthonormal Kautz filters, see Identification of Resonant Systems using Kautz Filters, Bo Wahlberg, Proceedings of the 30th Conference on Decision and Control, 1991, pages 2005-2010 .
- a further embodiment of the invention involves to use the delta-operator instead of the z-transform based shift operator in the filter implementation.
- the theory is described in for instance Sampling in digital signal processing and control, A. Feuer and G.C. Goodwin, Birkhauser, 1996 .
- the operating point may include the input derivative, amplitude, frequency and power, for instance.
- f (y; m) we consider the function f (y; m) to be continuous in m, so that we can tabulate different static non-linearities (SNL) and then interpolate between these.
- m t is a scalar mode parameter
- mode parameters we have found the following mode parameters to be of particular importance for tube modeling:
- FIG 10 shows an example of a non-linear function subject to hysteresis
- FIG 11 how the even and odd parts of this function, respectively, are well approximated by expansions using four basis functions.
- the weighting factor 1 / 1 ⁇ y 2 makes the polynomial more sensitive to catch the critical non-linearities around ⁇ 1, which is of utmost importance for audio applications.
- An important practical consequence is that relatively few basis functions are enough for accurate modeling, which facilities simulation, and that the softness of the basis functions turn out to eliminate the computational expansive over-sampling, which is usually needed to avoid unwanted harmonics when simulating non-linear functions.
- the DNL structure from the previous section is very flexible and efficient for modeling non-linear electric devices, but we still need a procedure to determine the parameters in the structure.
- these parameters are denoted ⁇ k ( t ) and ⁇ k ( t ) and are determined in the block labeled 'Create Coefficients'.
- f 0 the sampling interval T s and the number of data N such that f 0 is a multiple of 1/( NT s ).
- FFT fast Fourier transform
- k 0,1, 2, ...,1/( T s f 0 )
- the order K of the approximation can be chosen automatically by observing when the Fourier series coefficients become insignificant.
- Chebyshev polynomials can be theoretically justified for SNL modeling in general and tube modeling in particular as follows.
- Computer-based, or signal processor based, simulation of our model begins with a sample and hold circuit and an AD converter.
- the sample rate should of course exceed at least twice the bandwidth of the guitar signal to avoid aliasing.
- This simplified algorithm uses the peak value of the input amplitude over a sliding window L , but more sophisticated methods can be used.
- FIG 12 shows an example of modeling a tube, where the model for three different amplitudes and both hysteresis modes is illustrated.
- the operating point depends on the energy spectrum of the signal.
- a further alternative that has proven to work well for certain equipment as for instance loudspeakers, is to have separate non-linear functions to each frequency band, and then combine their outputs as z t ⁇ i f B i q y t .
- the signal flow is structured as in FIG 5 .
- the analog audio signal (502) is connected to an analog to digital interface (504), whose output (506) is communicatively coupled to a dynamic non-linearity (508).
- the output (514) of this dynamic non-linearity is finally communicatively coupled to an interface (516) producing the output audio signal (518).
- the dynamic non-linearity consists of a mode switching static non-linear function, where the mode parameter (512) is estimated in a function (510) based on the previous values on the input (506) and output (514) of the dynamic non-linearity.
- FIG 1 gives a more detailed description of signal flow.
- the audio signal u(t) is passed through a linear filter G pre (102), and the output is called y ( t ).
- the amplitude or RMS value of this output called ⁇ ( t ) is estimated (104), and the normalized filtered signal y ( t ) is computed (106).
- This signal's amplitude is passed through the static non-linear functions T k ( y ( t )) (110) and D k ( y ( t )) (112).
- a linear equalizer filter G eq (126) may be applied.
- a computer program for this embodiment may be structured according to FIG 2 .
- the program reads the audio signal from an analog to digital converter (A/D) (206), and writes a block of signal values to a buffer.
- This buffer is then processed by some equations emulating the linear part G pre (208).
- the program estimates the amplitude (210) and possibly the instantaneous frequency, normalizes the buffer (212), and from this finds an index to a look-up table (214) where the unique parameter values in the DNL are stored (216), which is repeated for each index k (218) in the DNL, and the parameter value to be used is then interpolated from neighboring points (220).
- the gain scheduling constant m to the DNL is computed (224) basis functions D k and T k (226,228) are then computed, which is repeated for each k (232), and these are weighted with the parameters ⁇ k and ⁇ k , respectively, and these terms are summed up.
- the buffer is then passed through some equations implementing a linear filter G eq (234) and finally the output is written to a D/A converter (236). The procedure is repeated (238) until the program ends (240).
- FIG 3 illustrates how several audio equipment emulators with different tuning can be put in series to emulate a complete amplifier, where for instance a guitar (302) is the connected to a pre-amplifier (304), which is connected to a power-amplifier (306) which in turn is connected to a loudspeaker (308).
- a guitar (302) is the connected to a pre-amplifier (304), which is connected to a power-amplifier (306) which in turn is connected to a loudspeaker (308).
- the invention is in one embodiment realized as an apparatus, method or computer program product devised for simulating linear parts of an audio equipment using stable basis expansions of the filter, such as Kautz filters and delta operators.
- This embodiment can be combined with any of the other optional features of the invention in accordance with the description and the claims.
- One further aspect of the invention in one embodiment is realized as an apparatus, method or computer program product devised for controlling the dynamics of linear parts of an audio equipment using multivariable interpolation techniques of higher order linear filters.
- This embodiment can be combined with any of the other optional features of the invention in accordance with the description and the claims.
- FIG 4 summarizes in a block diagram how the modeling is done.
- the gain scheduling parameter m is computed (430) for instance as instantaneous amplitude or frequency.
Description
- The present invention relates generally to a system for non-linear audio equipment simulation, and more specifically to the estimation of characteristic parameters in a model of such equipment and real-time simulation of this model.
- There are many kinds of audio equipment that show a non-linear behavior and then inherently are difficult to simulate. Microphones, pre-amplifiers, power-amplifiers and loud speaker cabinets are some examples of non-linear audio equipment. Of particular importance are the old-fashioned amplifiers used by for instance guitarists, that contain electronic vacuum tubes. Professional and amateur guitar players appreciate the sound of classic tube amplifiers. The warm sound of their dynamic distortion has turned out to be quite hard to mimic with transistor based amplifiers. In addition to a small second hand market of original amplifiers, so called re-issues are available commercially. The main drawbacks with these ones are: high price, high cost for spare parts (transformers, tubes, capacitors etc), large manufacturing variations between the tubes, high power consumption and the sometimes unpleasant fact that one has to use a high output level to get saturation and the required distortion. Another inherent drawback is that guitar players want to shift between different amplifiers and special effects, which require several cable re-connections or additional switching hardware, and a lot of expensive and space-requiring hardware.
- Therefore, several products exist today for simulating the tube distortion in analog electronics, or using software solutions in digital signal processors. Examples of this kind of technology are found in UK Patent
GB 2.040.632 US Patent 5.789.689 (M. Doidic, M. Mecca, M. Ryle, and C. Senffner, Tube modeling programmable digital guitar amplification system, August 1998, Line 6) andUS Patent 6,350,943 (K. Matsumoto, M.Suruga, and Y.Suzuki, Electric instrument amplifier, February 2002, Korg). The point is that the products become cheaper, smaller in size and much more flexible in that the user can switch between different amplifiers, pre-amps, loudspeaker models and additional effects (delay, echo, chorus, reverbation, equalizer, auto-volume and so on). However, when switching between these prior attempts of tube emulating systems and one of the original amplifiers they are said to mimic, musicians and even amateurs can hear the difference. - The task of modeling and simulating a dynamic system is a well-established area in engineering. This area is described in e.g. the text book L. Ljung and T. Glad, Modeling of dynamic systems (Prentice-Hall, 1996), where it is pointed out that there is no principal difference between modeling and simulation of economic and biologic systems, paper plants and electric systems. A dynamic system can be any physical or abstract process where one can observe its input and the outputs the process produces. Audio equipment and in particular a tube amplifier fits very well in this framework and is no exception to this general problem. The most critical problem is to find a good model of the dynamical system at hand, and if no physical model can be made, as is the case for the complicated nature of a tube amplifier, one should aim at estimating a model that fits observed input-output data from the system. This task is called system identification, and it is also a quite well established research area with long traditions for identifying models of dynamic systems, see the text books L. Ljung, System identification, Theory for the user (Prentice Hall, Englewood Cliffs, NJ, second edition, 1999), and T. Söderström and P. Stoica, System identification (Prentice Hall, New York, 1989) for instance, and the commercial software packages System Identification Toolbox for Matlab (The MathWorks, Inc, Natick, MA, 1999) and Frequency Identification Toolbox for Matlab (The MathWorks, Inc, Natick, MA, 1995). The general approach is as follows: Design an experiment and collect data from the dynamical system, here the guitar input and the output from the amplifier, for example the loudspeaker signal. 'Guess' a model structure (linear or non-linear discrete time filter, or a combination thereof). Use a numerical algorithm to adjust the free parameters in the model structure such that the discrepancy between the measured signals and model predictions are minimized. For linear systems, there is a variety of model structures and software tools to choose among. The theory of modeling linear dynamics is well-known and found in any text book in signal processing or modeling L. Ljung and T. Glad, Modeling of dynamic systems and J.G. Proakis and D.G. Manolakis, Digital signal processing - principles, algorithms and applications (Prentice-Hall International, New Jersey, 3 edition, 1996).
- For non-linear systems, for instance tube amplifiers, certain series connections of linear black box models with static non-linearities (SNL) (a so called Wiener model) have been suggested, see L. Ljung, System identification, Theory for the user and D. Atherton Nonlinear Control Engineering . This is also what has been used in previous art, such as
US patent 5.789.689 . A typical engineer in the system identification community would try several such structures, use standard software to identify free parameters in each structure from observed input-output data, and probably in the end find a fair approximation but conclude that no known standard structure is perfectly suitable for high-performance tube amplifiers. In prior art there is therefore a lack of satisfying models for simulating tube amplifiers in a natural sounding manner. Our findings is that standardized model structures consisting of series connection of linear dynamics and static non-linearities (SNL's) cannot model the complicated behavior of for instance tubes. - Audio equipment that can be controlled by potentiometers can be simulated in software by using a number of fixed filters, and then interpolating between these. A piece of prior art is the
US patent 6,222,110 , which describes a method for interpolating two second order filters. - The problem to be solved and the object of the invention is to provide an improved method and system for simulating audio equipment in general and tube amplifiers in particular, for instance those found in electric guitar equipment. Aspects of the problem are:
- To provide a general model structure of non-linear audio equipment that contains a set of characteristic parameters that can be changed to mimic amplifiers of different models and manufacturers.
- To provide a systematic way to estimate these parameters in an automatic procedure to quickly be able to model new amplifiers.
- A further aspect of the problem is to provide an efficient algorithm for simulating this model in real-time with short enough time delay.
- The invention is defined by the appended independent claims.
- In accordance with the present invention, the characteristic behavior of the audio equipment is modeled as a dynamic non-linearity (DNL), where a mode parameter decides which SNL should be active. This mode parameter can be interpreted as the operating point of the audio device and it may for instance include hysteresis effects and the temperature, measured as the recent energy.
- Further, the invention comprises a particular structure on the DNL, which is built up from a linear combination of a basis for the SNL, where the so called Chebyshev polynomial basis is one possible choice. This gives many practical advantages for both identification and simulation performance, as will be described later. An important consequence, compared to related art, is that the particular structure that is used does not require over-sampling.
- The invention also comprises an efficient identification experiment for estimating the coefficients in the Chebyshev expansion, or any other basis expansion, of the DNL. In conclude that no known standard structure is perfectly suitable for high-performance tube amplifiers. In prior art there is therefore a lack of satisfying models for simulating tube amplifiers in a natural sounding manner. Our findings is that standardized model structures consisting of series connection of linear dynamics and static non-linearities (SNL's) cannot model the complicated behavior of for instance tubes
- Audio equipment that can be controlled by potentiometers can be simulated in software by using a number of fixed filters, and then interpolating between these. A piece of prior art is the
US patent 6,222,110 , which describes a method for interpolating two second order filters. - The problem to be solved and the object of the invention is to provide an improved method and system for simulating audio equipment in general and tube amplifiers in particular, for instance those found in electric guitar equipment. Aspects of the problem are:
- To provide a general model structure of non-linear audio equipment that contains a set of characteristic parameters that can be changed to mimic amplifiers of different models and manufacturers.
- To provide a systematic way to estimate these parameters in an automatic procedure to quickly be able to model new amplifiers.
- A further aspect of the problem is to provide an efficient algorithm for simulating this model in real-time with short enough time delay.
- In accordance with the present invention, the characteristic behavior of the audio equipment is modeled as a dynamic non-linearity (DNL), where a mode parameter decides which SNL should be active. This mode parameter can be interpreted as the operating point of the audio device and it may for instance include hysteresis effects and the temperature, measured as the recent energy.
- Further, the invention comprises a particular structure on the DNL, which is built up from a linear combination of a basis for the SNL, where the so called Chebyshev polynomial basis is one possible choice. This gives many practical advantages for both identification and simulation performance, as will be described later. An important consequence, compared to related art, is that the particular structure that is used does not require over-sampling.
- The invention also comprises an efficient identification experiment for estimating the coefficients in the Chebyshev expansion, or any other basis expansion, of the DNL. In accordance with the invention inputting sinusoids of different amplitudes is sufficient for estimation of these coefficients, and it is shown that these are related to the Fourier series expansion of the measured output of the audio equipment, enabling efficient algorithms, such as the fast Fourier transform (FFT) or more dedicated algorithms to be used.
- The present disclosure describes an apparatus for software or hardware emulation of electronic audio equipment, which characterizes a non-linear behavior. The invention comprises an analog to digital interface (504) for the input audio signal (502), whose output (506) is communicatively coupled to a dynamic non-linearity (508). The output (514) of this dynamic non-linearity is finally communicatively coupled to an interface (516) producing the output audio signal (518). The dynamic non-linearity consists of mode switching static non-linear function, where the mode parameter (512) is estimated in a function (510) based on the previous values on the input (506) and output (514) of the dynamic non-linearity.
- In another embodiment of the present disclosure, a linear filter is used to change the frequency content of the interfaced audio signal (504) before it is coupled to the DNL (508). Yet another linear filter can be used on the DNL's output (514) to change the audio output frequency characteristics.
- It has been validated that this structure is particularly well suited for emulation of guitar tube amplifiers, where the dynamic non-linearity models the complicated tube behavior, whose characteristics can be explained by the operating mode of the tube which physically may be explained by one or more of the following quantities of the input signal: energy, amplitude, hysteresis and frequency.
- The present invention will be further explained by means of exemplifying embodiments in conjunction with the accompanying drawings, in which:
-
FIG 1 shows a block diagram showing the structure of the simulation. -
Fig 2 shows a flowchart of the simulation. -
FIG 3 shows a block diagram illustrating the audio equipment model. The physical amplifier box is replaced by a simulation of the signal zt from its input ut . A similar methodology applies to the power-amplifier and loudspeaker. -
FIG 4 shows a block diagram illustrating an embodiment of the invention applied for estimation of the model. -
FIG 5 shows a block diagram illustrating an embodiment of the invention applied for emulation of the modeled audio equipment. -
FIG 6 shows the first four orthonormalized polynomial basis functions. -
FIG 7 shows the first four Chebyshev basis functions. -
FIG 8 shows a typical non-linear function. -
FIG 9 shows the weighted Chebyshev basis functions inFIG 3 , weighted with respect to the SNL inFIG 4 , while the lower plot shows the approximation and function itself. -
FIG 10 shows a non-linear function subject to hysteresis. -
FIG 11 shows a the even and odd functions of the non-linear functions inFig 6 , and the corresponding Chebyshev expansion model. -
FIG 12 shows an array of SNL for different mode parameters. - The invention is based on a model of first the linear parts and then a dynamic non-linear model structure for the non-linear devices, identification of the free parameters in this non-linear model structure and finally a way to simulate this model. The total audio equipment emulator is outlined in
FIG 1 . - Though the invention applies to a range of audio equipment, we will sometimes speak of a particular application of simulating a tube pre-amplifier as illustrated in
FIG 6 . Here a guitar (302) is connected to a pre-amplifier (304), whose output is power amplified (306) and fed to the speakers (308). This is just for illustrative purposes, and a tube can be seen to be a typical non-linear audio equipment in this context. - The invention comprises a method and a realization of the method that may be realized in hardware, software or a combination thereof. The most feasible realization of the invention is likely to be in the shape of a computer program product preferably comprising a data carrier provided with program code or other means devised to control or direct a data processing apparatus to perform the method steps and functions in accordance with the description. A data processing apparatus running the inventive method typically includes a central processing unit, data storage means and an I/O-interface for signals or parameter values. The invention may also be realized as specifically designed hardware and software in an apparatus or a system comprising mechanisms and functional stages or other means carrying out the method steps and functions in accordance with the description.
- An embodiment of the invention comprises modeling of linear parts in the electronic device, denoted Gpre (102) in
FIG 1 . The modeling of linear dynamics is preferably carried out in a per se known manner, for example shown in the above cited prior art. - The parts of the amplifier that include only passive components like resistors and capacitors, can be modeled theoretically with high accuracy, at least if all component values are known. The procedure to model and simulate the linear part is well-known from for instance the text books above, but is an important preliminary step for this invention. First, the electrical circuit with passive components will provide a continuous time filter. In accordance with an embodiment of the invention, the modeling will provide a continuous time filter G(s; vnom ),
- Since a digital implementation is used, this model can be converted to a discrete time model H(z; θ). Here z = ei2πf is the z-transform operator and θ is the vector of parameters in the transfer function, which takes the form
- This is fine if the component values are known exactly, and if the circuit diagram is available. Consider first the case when a circuit diagram is available, but the component values are uncertain, or have been changed by the owner. There are two main approaches for finding the correct values. The first method works in the time domain, cf. e.g. the prior art book L. Ljung, System identification, Theory for the user. Generate an arbitrary input signal, usually random numbers, and collect the signals ut, yt . Then adjust the parameters so that the model predictions are minimized
- Computing the structure in equation (1) and then equation (2) from a circuit scheme is a quite tedious task to do for each new amplifier that is going to be modeled. An alternative used in an embodiment of the invention is to establish a general black-box model of the form as in equation (2), where one guesses or uses model selection criteria to choose m and n, collect input-output data in an identification experiment and then estimate the parameters with standard methods, for instance available in the system identification or frequency domain identification toolboxes in Matlab. This will provide an H(z; θ).
- A flexible linear part in an electronic device, Gpre (102) and Geq (126) in
FIG 1 , can be controlled by the user by turning potentiometers. Such a change influences all coefficients in the filter H(z) in Equation (2), which thus has to be recalculated. One way to avoid this, is to compute the filter H(z) for a number of potentiometer settings, and then interpolate between these. This is important for equalizers and tonestacks, which usually have 3-4 different potentiometers controlling the tone. Another interesting application is to let a pedal or the output from another control unit replace the potentiometers. Still, the linear filter should be interpolated from tabled filters. Below, an accurate method with little memory requirement is described. - In one dimension (one potentiometer), the theory is simple. Let the potentiometer value be represented by 0 ≤ u ≤ 1, and suppose we have computed the filter H(z; ui ) for i = 1, 2, ..., n. The user then chooses u such that uk ≤ u ≤ u k+1. The interpolated filter is then
-
- Still, the number of pre-computed filter coefficients that need to be stored in memory is too high. Ten different potentiometer settings for four potentiometers implies 104 set of filter coefficients. Another embodiment of the invention is to use very few potentiometer settings, for instance only 2, and include a scalar pre-compensation function ui = fi (ui ) for each potentiometer i = 1, 2, 3, ..., K. That is, first each potentiometer setting, ui is first transformed by a one-dimensional non-linear function fi , then a multidimensional interpolation is applied using the compensated potentiometer settings. The non-linear function fi is preferably stored as a table and one-dimensional interpolation applied. Here, only 24 different coefficient sets need to be pre-computed and stored in memory. Practice has shown that audio equipment as tone stacks are interpolated very accurately with this method.
- The linear parts in the electronic device, denoted Gpre (102) and Geq (126) in
FIG 1 , are subject to numerical ill-conditioning. Simulating Equation (2) can result in an unstable output, or at least not as accurate as desirable. This is in particular a problem for highly resonant audio devices as loudspeakers. An embodiment of the invention comprises the use of numerically robust basis functions and delta operators as outlined below. - It is wellknown that any linear transfer function can be described as a sum of a basis function expansion. The basis functions can for instance be second order orthonormal Kautz filters, see Identification of Resonant Systems using Kautz Filters, Bo Wahlberg, Proceedings of the 30th Conference on Decision and Control, 1991, pages 2005-2010. The Kautz basis is a set of second order filters of the form
- A further embodiment of the invention involves to use the delta-operator instead of the z-transform based shift operator in the filter implementation. This can also be seen as a different basis, where the in signal processing dominating z-transform variable is replaced by δ = (z - 1)/T, where T is the sampling interval. The theory is described in for instance Sampling in digital signal processing and control, A. Feuer and G.C. Goodwin, Birkhauser, 1996.
- After all linear parts in the electronic device are modeled according to the previous section, we next focus on the non-linear parts. In this section, we propose a non-linear dynamic model structure which is very efficient in modeling non-linear electronic devices The idea is to consider the electric device as a black box with input ut and output yt, and model what is in between.
- In fully controlled experiments, we can generate arbitrary ut and collect the device's output zt . Due to the sensitive feedback loops in for instance tubes, we cannot put a probe into the amplifier and measure the tube input yt directly. However, using the linear model from the previous section, we can compute yt = H(q; θ̂)ut and use this instead. The question now is what structure to use for the DNL. We propose the following one
- The hysteresis mode ht defined by
- The energy, amplitude or peak value of the signal yt during the last few milliseconds. We denote this mode parameter At, since it is related to the amplitude of the input. This is an empirical observation from experiments, but could be motivated by the temperature sensitivity of the tube characteristics or fluctuations in the voltage from the power supply.
-
- We next need a structure for each SNL z = f(y). Since this structure will be the same for each mode parameter, it will in the sequel be suppressed. Consider an arbitrary basis Pk (y) for a general class of functions defined on the interval -1 ≤ y ≤ 1. These so called Legendre polynomials satisfy by the definition of an orthonormal basis the orthonormality conditions
FIG 6 . -
- Now, hysteresis implies that we have two SNL's, one for h = 1 and one for h = -1. Denote these two SNL's fh (y). We can from these define the even and odd SNL's by
- Estimation of the coefficients can be done with standard least squares algorithms, by noting that equation (23) can be written as a linear regression model
-
FIG 10 shows an example of a non-linear function subject to hysteresis, andFIG 11 how the even and odd parts of this function, respectively, are well approximated by expansions using four basis functions. - We will motivate in several ways why a Chebyshev polynomial expansion is an ingenious way for modeling tube behavior. First, the definition of these polynomials, here called P̅k (y), is
weighting factor FIG 7 . - These basis functions can be written explicitly. It is standard in literature and convenient for further discussion to split the basis function P̅k (y) into one basis Tk (y) for all odd functions on [-1,1] and one basis Dk (y) for all even functions on [-1,1]. These are then given by
FIG 1 , the input to the DNL is y, the DNL is represented by by blocks Tk and Dk, and z is its output. - The
weighting factor - The DNL structure from the previous section is very flexible and efficient for modeling non-linear electric devices, but we still need a procedure to determine the parameters in the structure. Here we describe how the parameters in the DNL can be computed from measured inputs ut and outputs yt. In
FIG 1 , these parameters are denoted α̂k (t) and β̂k (t) and are determined in the block labeled 'Create Coefficients'. - The general identification problem is to first design the input ut and then to find an algorithm for fitting αk (A, h) in equation (23) to the observed data. Because of the new concept of a DNL, there is no available standard software for this problem. We suggest to use inputs ut such that yt = A cos(2πf 0). This is achieved by
- It can be proven that the Fourier series coefficients of zt with a sinusoid as the input correspond to the coefficients αk , βk in the expansion (30) (again omitting the mode parameter for brevity), so we can compute them theoretically for a given function f (y) as
0 k ) for k = 0,1, 2, ...,1/(Tsf 0), and let - The choice of Chebyshev polynomials can be theoretically justified for SNL modeling in general and tube modeling in particular as follows. The polynomial
weighting factor - The previous sections have first suggested a new dynamic non-linear (DNL) model structure and how to estimate the free parameters. We now describe in detail how the DNL can be simulated efficiently, which is the final step in emulating a non-linear electronic device according to our invention.
- Computer-based, or signal processor based, simulation of our model begins with a sample and hold circuit and an AD converter. Design issues include the choice of sample rate fs = 1/Ts and the number of quantization bits. How this should be done is described in any text book in signal processing, see e.g. the text books J.G. Proakis and D.G. Manolakis, Digital signal processing - principles, algorithms and applications and F. Gustafsson, L. Ljung, and M. Millnert, Signalbehandling (Studentlitteratur, in Swedish, 2000). The sample rate should of course exceed at least twice the bandwidth of the guitar signal to avoid aliasing.
- Simulation of linear discrete time dynamical systems (filter) as H(z, θ̂) is a standard procedure and does not deserve any particular comments, other than that the sample rate fs = 1/Ts should be chosen high enough compared to the bandwidth of the filter.
-
- It is well-known that a non-linear function creates harmonics of the input signals. This is mostly a desired consequence and is needed to get the soft distortion of the tubes, as well as the attack during the transients. Of course, if these harmonics exceed the Nyqvist frequency fs /2, they will be aliased and the sound quality will deteriorate. The standard procedure described in text books is to oversample the input signal and then anti-alias filter and decimate the output zt . Oversampling can be done either after the linear filters at yt, or by choosing high enough a sample rate of ut in the first place. However, we have found that the smooth form of the Chebyshev basis functions create very little unwanted high frequency harmonics, and this is probably a problem that occurs mainly if look-up tables and interpolation are used to represent a SNL f(y).
-
FIG 12 shows an example of modeling a tube, where the model for three different amplitudes and both hysteresis modes is illustrated. - As an alternative to the DNL, a filter bank approach can be used, where the energy in each frequency interval controls the dynamic non-linearity. A filter bank is defined by a set of band-pass filters
-
- This can be seen as an alternative to (14).
- To sum up, in one embodiment of the invention, the signal flow is structured as in
FIG 5 . The analog audio signal (502) is connected to an analog to digital interface (504), whose output (506) is communicatively coupled to a dynamic non-linearity (508). The output (514) of this dynamic non-linearity is finally communicatively coupled to an interface (516) producing the output audio signal (518). The dynamic non-linearity consists of a mode switching static non-linear function, where the mode parameter (512) is estimated in a function (510) based on the previous values on the input (506) and output (514) of the dynamic non-linearity. -
FIG 1 gives a more detailed description of signal flow. First, the audio signal u(t) is passed through a linear filter Gpre (102), and the output is called y(t). The amplitude or RMS value of this output called Â(t) is estimated (104), and the normalized filtered signaly (t) is computed (106). This signal's amplitude is passed through the static non-linear functions Tk (y (t)) (110) and Dk (y (t)) (112). At the same time, the signal amplitude Â(t) looks up the parameters α̂k (t) and β̂k (t) (116) in an interpolation table (108), and the weighted sum z(t) = Σ k α̂k (t)Tk (y (t)) + h(t)β̂ k (t)Dk (y (t)) is computed (124). Finally, a linear equalizer filter Geq (126) may be applied. - A computer program for this embodiment may be structured according to
FIG 2 . After initialization (204), the program reads the audio signal from an analog to digital converter (A/D) (206), and writes a block of signal values to a buffer. This buffer is then processed by some equations emulating the linear part Gpre (208). Then the program estimates the amplitude (210) and possibly the instantaneous frequency, normalizes the buffer (212), and from this finds an index to a look-up table (214) where the unique parameter values in the DNL are stored (216), which is repeated for each index k (218) in the DNL, and the parameter value to be used is then interpolated from neighboring points (220). - The gain scheduling constant m to the DNL is computed (224) basis functions Dk and Tk (226,228) are then computed, which is repeated for each k (232), and these are weighted with the parameters αk and βk, respectively, and these terms are summed up. The buffer is then passed through some equations implementing a linear filter Geq (234) and finally the output is written to a D/A converter (236). The procedure is repeated (238) until the program ends (240).
-
FIG 3 illustrates how several audio equipment emulators with different tuning can be put in series to emulate a complete amplifier, where for instance a guitar (302) is the connected to a pre-amplifier (304), which is connected to a power-amplifier (306) which in turn is connected to a loudspeaker (308). - Furthermore, the invention is in one embodiment realized as an apparatus, method or computer program product devised for simulating linear parts of an audio equipment using stable basis expansions of the filter, such as Kautz filters and delta operators. This embodiment can be combined with any of the other optional features of the invention in accordance with the description and the claims.
- One further aspect of the invention in one embodiment, is realized as an apparatus, method or computer program product devised for controlling the dynamics of linear parts of an audio equipment using multivariable interpolation techniques of higher order linear filters. This embodiment can be combined with any of the other optional features of the invention in accordance with the description and the claims.
-
FIG 4 summarizes in a block diagram how the modeling is done. - First, all passive components (402) form a linear system, where a linear model H(q; θ) (420) is estimated using standard system identification techniques (420) using the model error signal yt - ŷt (412).
- Second, the non-linear parts as tubes (404) are modeled by the proposed new DNL structure z = f(y; m, α) (422), where a tailored new system identification algorithm (414) is applied to estimate the free parameters α using the error signal zt - ẑt (416). The gain scheduling parameter m is computed (430) for instance as instantaneous amplitude or frequency.
Claims (14)
- An apparatus for emulation of electronic non-linear audio equipment comprising:an input interface (504) for receiving an audio signal (502) and producing a first signal (506),a dynamic and non-linear device (508) comprising static non-linear functions, and arranged such that two mode parameters (512) decide which static non-linear function isactive, said dynamic and non-linear device (508) being further arranged to operate on said first signal (506) and produce a second signal (514),a mode estimator (510) arranged to operate on said first signal as input, identify an operating mode for the dynamic and non-linear device (508) and accordingly provide said two mode parameters to an output (512) of said mode estimator (510) being communicatively coupled to said dynamic and non-linear device (508), andan interface (516) for outputting said second signal (514) as an output audio signal (518),characterized in that said two mode parameters consist of a first mode parameter related to hysteresis and of a second mode parameter related to input energy, or amplitude, the dynamic and non-linear device (508) being arranged to provide the second signal (514) as a function depending on said first signal (504) and said two mode parameters, the function being continuous in said two mode parameters with said static non-linear functions being tabulated and interpolated, and with said two mode parameters deciding which static non-linear function is operating on the first signal and providing the second signal.
- The apparatus as recited in claim 1, wherein the mode estimator is additionally arranged to operate on the second signal as input.
- The apparatus as recited in any one of claims 1-2, wherein a basis expansion using Chebyshev polynomials is used for the static functions in the dynamic and
nonlinear device (508). - The apparatus as recited in claim 3, wherein one basis expansion for each mode parameter is tabled, and table lookup is used in the emulation.
- The apparatus as recited in claim 1, wherein the outputs of a filter bank are used to control the dynamic and non-linear device (508).
- The apparatus as recited in claim 1, wherein a linear filter is used to shape the frequency characteristics of the input audio signal (502) before being inputted to the dynamic and non-linear device (508).
- The apparatus as recited in claim 1, where a linear filter is used to shape the frequency characteristics of the output signal (514) from the dynamic and non-linear device (508) (508) before being interfaced (516) to an audio signal (518).
- The apparatus as recited in claim 1, wherein a tailored excitation signal is used for automatically identifying parameters in the static non-linear functions.
- The apparatus as recited in claim 3, wherein
a tailored excitation signal is used for automatically identifying parameters in the static non-linear functions; and
sinusoids with different amplitudes and frequencies are used as input to identify series expansion coefficients of the basis expansion. - The apparatus as recited in claim 1, further being adapted for simulation of a guitar tube amplifier.
- The apparatus as recited in claim 1, further being adapted for simulation of a microphone.
- The apparatus as recited in claim 1, further being adapted for simulation of a loudspeaker.
- A method for emulation of electronic non-linear audio equipment comprising the steps of:receiving an audio signal (502) by means of an input interface (504) and producing a first signal (506);providing a dynamic and non-linear device (508) comprising static non-linear functions, the dynamic and non-linear device (508) operating on said first signal (506),producing a second signal (514) and deciding by means of two mode parameters (512) which static non-linear function is active;providing a mode estimator (510), the mode estimator operating on said first signal as input, identifying an operating mode for the dynamic and non-linear device (508) and accordingly providing said two mode parameters to an output (512) of said mode estimator (510) being communicatively coupled to said dynamic and non-linear device (508); andoutputting said second signal (514) as an output audio signal (518) by means of an interface (516);characterized in that said two mode parameters consist of a first mode parameter related to hysteresis and a second mode parameter related to input energy, or amplitude, the dynamic and non-linear device (508) providing the second signal (514) as a function depending on said first signal (504) and said two mode parameters, the function being continuous in said two mode parameters with said static non-linear functions being tabulated and interpolated, and with said two mode parameters deciding which static non-linear function is operating on the first signal and providing the second signal.
- A computer program product comprising program code adapted to direct a data processing system to perform the steps according to claim 13.
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Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP4747835B2 (en) * | 2005-12-27 | 2011-08-17 | ヤマハ株式会社 | Audio reproduction effect adding method and apparatus |
US20070168063A1 (en) * | 2006-01-18 | 2007-07-19 | Gallien Robert A | Programmable tone control filters for electric guitar |
JP5049292B2 (en) | 2006-11-20 | 2012-10-17 | パナソニック株式会社 | Signal processing apparatus and signal processing method |
US20090080677A1 (en) * | 2007-09-24 | 2009-03-26 | Webster Stephen P | Stringed instrument with simulator preamplifier |
KR20130051413A (en) * | 2011-11-09 | 2013-05-20 | 삼성전자주식회사 | Apparatus and method for emulating sound |
CN104252559B (en) * | 2014-08-29 | 2018-04-17 | 浙江中科电声研发中心 | A kind of Numerical Simulation Analysis method of loudspeaker multi- scenarios method |
US9823898B2 (en) * | 2015-09-30 | 2017-11-21 | Harman International Industries, Incorporated | Technique for determining nonlinear order-separated responses of nonlinear systems including linear response at system typical input levels |
CN107995193B (en) * | 2017-12-02 | 2020-06-02 | 宝牧科技(天津)有限公司 | Method for detecting network abnormal attack |
EP3783600B1 (en) * | 2018-04-19 | 2023-03-15 | Roland Corporation | Electric musical instrument system |
US10846489B2 (en) | 2018-07-23 | 2020-11-24 | Sendyne Corporation | Analog computing implementing arbitrary non-linear functions using Chebyshev-polynomial-interpolation schemes and methods of use |
WO2020084401A1 (en) * | 2018-10-26 | 2020-04-30 | Sendyne Corporation | Improved runtime-calibratable analog computing system and methods of use |
CN114705286A (en) * | 2022-04-02 | 2022-07-05 | 厦门亿联网络技术股份有限公司 | Method and device for detecting machine seismic sound, computer and readable storage medium |
JP2024022790A (en) * | 2022-08-08 | 2024-02-21 | 株式会社日立製作所 | Design support method and design support device |
Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20020005108A1 (en) * | 1998-05-15 | 2002-01-17 | Ludwig Lester Frank | Tactile, visual, and array controllers for real-time control of music signal processing, mixing, video, and lighting |
Family Cites Families (24)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
GB2040632B (en) | 1979-01-25 | 1983-11-23 | Hartley P | Sound amplifiers |
US5434536A (en) | 1987-03-23 | 1995-07-18 | Pritchard; Eric K. | Semiconductor emulation of vacuum tubes |
US4809336A (en) | 1987-03-23 | 1989-02-28 | Pritchard Eric K | Semiconductor amplifier with tube amplifier characteristics |
US4868869A (en) * | 1988-01-07 | 1989-09-19 | Clarity | Digital signal processor for providing timbral change in arbitrary audio signals |
US4991218A (en) * | 1988-01-07 | 1991-02-05 | Yield Securities, Inc. | Digital signal processor for providing timbral change in arbitrary audio and dynamically controlled stored digital audio signals |
US5248844A (en) * | 1989-04-21 | 1993-09-28 | Yamaha Corporation | Waveguide type musical tone synthesizing apparatus |
US5144096A (en) * | 1989-11-13 | 1992-09-01 | Yamaha Corporation | Nonlinear function generation apparatus, and musical tone synthesis apparatus utilizing the same |
JPH03184095A (en) * | 1989-12-14 | 1991-08-12 | Yamaha Corp | Electronic musical instrument |
JPH0778679B2 (en) * | 1989-12-18 | 1995-08-23 | ヤマハ株式会社 | Musical tone signal generator |
JPH087588B2 (en) * | 1990-01-16 | 1996-01-29 | ヤマハ株式会社 | Music control device |
JP2504298B2 (en) * | 1990-06-20 | 1996-06-05 | ヤマハ株式会社 | Music synthesizer |
US5241692A (en) * | 1991-02-19 | 1993-08-31 | Motorola, Inc. | Interference reduction system for a speech recognition device |
JPH06342287A (en) | 1993-06-02 | 1994-12-13 | Yamaha Corp | Effect device |
US6760451B1 (en) * | 1993-08-03 | 2004-07-06 | Peter Graham Craven | Compensating filters |
US5680450A (en) * | 1995-02-24 | 1997-10-21 | Ericsson Inc. | Apparatus and method for canceling acoustic echoes including non-linear distortions in loudspeaker telephones |
US5789689A (en) * | 1997-01-17 | 1998-08-04 | Doidic; Michel | Tube modeling programmable digital guitar amplification system |
JP3983364B2 (en) | 1998-01-20 | 2007-09-26 | ローランド株式会社 | Digital modulator |
US6208969B1 (en) * | 1998-07-24 | 2001-03-27 | Lucent Technologies Inc. | Electronic data processing apparatus and method for sound synthesis using transfer functions of sound samples |
US6504935B1 (en) * | 1998-08-19 | 2003-01-07 | Douglas L. Jackson | Method and apparatus for the modeling and synthesis of harmonic distortion |
JP3621017B2 (en) | 2000-03-24 | 2005-02-16 | 第一工業製薬株式会社 | Polyurethane resin for filter seal |
WO2002003377A1 (en) | 2000-07-05 | 2002-01-10 | Koninklijke Philips Electronics N.V. | Method of calculating line spectral frequencies |
US6350943B1 (en) | 2000-12-28 | 2002-02-26 | Korg, Inc. | Electric instrument amplifier |
US6664460B1 (en) * | 2001-01-05 | 2003-12-16 | Harman International Industries, Incorporated | System for customizing musical effects using digital signal processing techniques |
US6881891B1 (en) * | 2002-07-16 | 2005-04-19 | Line 6, Inc. | Multi-channel nonlinear processing of a single musical instrument signal |
-
2003
- 2003-06-23 SE SE0301790A patent/SE0301790L/en not_active IP Right Cessation
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2004
- 2004-06-18 EP EP04102813.5A patent/EP1492081B1/en not_active Not-in-force
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Patent Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20020005108A1 (en) * | 1998-05-15 | 2002-01-17 | Ludwig Lester Frank | Tactile, visual, and array controllers for real-time control of music signal processing, mixing, video, and lighting |
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